Analyze the structure of reasons for purchasing shampoo brands with causal inference analysis, which reveals highly accurate causal structures with an automated causal structure visualization process.

【 Summary 】

Conventional causal inference analysis involves SEM (covariance structure analysis), but this is a complicated analysis method that requires prior examination of the hypothesized path structure and requires statistical knowledge to analyze.
Macromill, Inc.’s causal inference analysis “causal analysis for Macromill” is a system that can read and analyze multiple variables without hypothesizing a path structure diagram using a proprietary algorithm.
In this study, we used this system to conduct a causal structure analysis with shampoo brand favorability as the objective variable.
The purpose of the analysis was to clarify the causal structure of brand favorability and to link it to communication measures such as the brand image.
The results of the analysis based on the information obtained from the questionnaire revealed that “high evaluation of beauticians and professionals” was the most important factor leading to the level of brand favorability.